Machine learning Mitchell, Tom M

By:

Mitchell, Tom M

Material type: Text

TextPublication details: Chennai : McGraw Hill Education India Pvt. Ltd, 2013.Description: xvii, 414pISBN:

9781259096952

DDC classification:

006.31 MIT

Contents:

Chapter 1. Introduction Chapter 2. Concept Learning and the General-to-Specific Ordering Chapter 3. Decision Tree Learning Chapter 4. Artificial Neural Networks Chapter 5. Evaluating Hypotheses Chapter 6. Bayesian Learning Chapter 7. Computational Learning Theory Chapter 8. Instance-Based Learning Chapter 9. Inductive Logic Programming Chapter 10. Analytical Learning Chapter 11. Combining Inductive and Analytical Learning Chapter 12. Reinforcement Learning.

Summary: Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data. Tags from this library: No tags from this library for this title

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Item type	Current library	Collection	Call number	Status	Barcode
Books	IIITDM Kurnool COMPUTER SCIENCE ENGINEERING	Non-fiction	006.31 MIT (Browse shelf(Opens below))	Available	0007432
Books	IIITDM Kurnool COMPUTER SCIENCE ENGINEERING	Non-fiction	006.31 MIT (Browse shelf(Opens below))	Available	0007433

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Chapter 1. Introduction
Chapter 2. Concept Learning and the General-to-Specific Ordering
Chapter 3. Decision Tree Learning
Chapter 4. Artificial Neural Networks
Chapter 5. Evaluating Hypotheses
Chapter 6. Bayesian Learning
Chapter 7. Computational Learning Theory
Chapter 8. Instance-Based Learning
Chapter 9. Inductive Logic Programming
Chapter 10. Analytical Learning
Chapter 11. Combining Inductive and Analytical Learning
Chapter 12. Reinforcement Learning.

Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.
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